1. Field of the Invention
This invention concerns image analysis of video signals or data in order to detect prior, block-based processing and to quantify block-related picture impairments.
2. Description of the Related Art
It is very common for video or image processing techniques to make use of “block-based” processing in which the image is divided into equal sized regions and the pixels within each region are processed together. A good example is the video compression method in which a transform is applied separately to each of a regularly structured set of blocks of pixels and each block is represented (for transmission or storage) by a set of transform coefficients. When different processing is applied to the different blocks, for example different quantisation of transform coefficients, the block structure can become visible as an image artefact because the spatial frequency response of the transmission system varies from block to block.
In broadcasting and multimedia content creation and distribution it is frequently desirable to check the subjective quality of video and image data, and in particular, automatic methods of assessing subjective quality are increasingly being sought for economic reasons. Video quality analysis methods fall into two types: “double-ended” methods where the processed images are compared with unprocessed images to identify artefacts; and, “single-ended” methods in which the processed images are analysed without reference to unprocessed images. Double-ended methods are usually only applicable to a research and development environment; single-ended methods are preferable in normal commercial production and distribution operations.
There are a number of known methods for automatically analysing subjective “blockiness” or block artefacts. In this context, “blockiness” or block artefacts are a measure of the subjective impairment of the images due to the block-based processing. Generally these methods require prior knowledge of the positions of the block boundaries or the size of the blocks. For example: if the boundary positions are known, average luminance or chrominance differences can be evaluated across the boundaries; and, if the size of the blocks is known, inter-pixel differences can be evaluated in a repeating pattern with a periodicity equal to the block size.
The need for prior knowledge of the block structure severely limits the usefulness of these methods. It is not unusual for images to undergo spatial transformations, such as aspect ratio-conversion in which the block size is changed; these processes may be cascaded and block-based compression or processing may be applied at any point in the signal chain. An image may therefore have been subjected to a number of different block-based processes with arbitrary block sizes and boundary positions; and, there may be more than one set of block-based artefacts present with different block structures for the different sets of artefacts.
One known approach is shown in WO 2007/125286 to which reference is directed.
It is also important, particularly if large numbers of channels are to be monitored from this and other quality aspects, for the block size to be determined accurately but in a manner which makes efficient use of processing resources. If the monitoring is to be performed in real-time, it is usually also important for the delay or latency that is introduced by the processing to be as small as possible. Once a block size has been determined—this itself of course indicating the past block-processing of the video—a variety of techniques, including the known techniques mentioned above, may be employed for quantifying block based artefacts.